class_docstr: Scheme-based registry for model evaluator implementations
docstr: Get an evaluator instance from the registry based on the name of evaluator
docstr_tok: ["Get","an","evaluator","instance","from","the","registry","based","on","the","name","of","evaluator"]
code: def get_evaluator(self, evaluator_name):
      """
      Get an evaluator instance from the registry based on the name of evaluator
      """
      evaluator_cls = self._registry.get(evaluator_name)
      if evaluator_cls is None:
          raise MlflowException(
              f"Could not find a registered model evaluator for: {evaluator_name}. "
              f"Currently registered evaluator names are: {list(self._registry.keys())}"
          )
      return evaluator_cls()
  
file_path: mlflow/mlflow/models/evaluation/evaluator_registry.py
imports: import warnings
  import entrypoints
  from mlflow.exceptions import MlflowException
  from mlflow.utils.import_hooks import register_post_import_hook
label_desc: Use image node_id 4 for calling the ModelEvaluatorRegistry obj's underlying member method code with example usage: obj.get_evaluator(evaluator_name) and returns: evaluator_cls